The contribution of this paper lies in providing a general method for obtaining distributed control laws akin to the specialized implementations from [1]}, i.e., distributed implementations that explicitly avoid the communication of internal states (controller or plant states) between the sub-controllers. The proposed method relies on the concept of Network Realization Functions (NRF) introduced here, able to impose sparsity constraints directly on the distributed controller's coprime factors, thus bypassing the aforementioned drawbacks mentioned in points (a) and (b) and guaranteeing the full scalability of the distributed control laws for possibly unstable plants. En route, we point out that NRF representations of Linear and Time-Invariant (LTI) networks are able to simultaneously capture both the dynamics and the topology of the network and are valid in both the discrete- and continuous-time [2]}, [3]}, while also explicitly avoiding any self-loops (integrators or delay elements) on the manifest control signals. Finally, the close affinity between (doubly) coprime factorizations and NRFs allows for a natural exploitation of the powerful robust stabilization machinery for distributed controller design, as established in [3]}. While not explicitly construed here, the main ideas of this paper bear the influence of the celebrated "behavioral approach" from [5]}.
